Beyond WEIRD Legal AI: Why Concept-Based Models Outperform Token-Based Approaches

Archived open-access copy of a working paper previously listed in the SSRN archive of the Lerer research program. Original SSRN record: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5576850. This Zenodo record is part of a consolidation pass from SSRN-hosted PDFs to durable Zenodo records.

Authors

Ignacio Adrián LERER (ORCID: https://orcid.org/0009-0007-6378-9749)

Publication Details

Journal: Zenodo (CERN European Organization for Nuclear Research)
Published: 2026-06-09
DOI: https://doi.org/10.5281/zenodo.20612853
Primary Topic: Artificial Intelligence in Law
Type: preprint

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preprint

Beyond WEIRD Legal AI: Why Concept-Based Models Outperform Token-Based Approaches

Ignacio Adrián LERER

Jun 9, 2026

Zenodo (CERN European Organization for Nuclear Research)

Artificial Intelligence in Law

preprint

Beyond WEIRD Legal AI: Why Concept-Based Models Outperform Token-Based Approaches

Ignacio Adrián LERER

June 9, 2026preprint en

Abstract

Zenodo (CERN European Organization for Nuclear Research)

Artificial Intelligence in Law

DOI Open Access PDF OpenAlex

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Beyond WEIRD Legal AI: Why Concept-Based Models Outperform Token-Based Approaches — Ignacio Adrián LERER · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS